Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review
Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …
cognitive load by bridging the gap between the task-at-hand and relevant information by …
Recent advancements in end-to-end autonomous driving using deep learning: A survey
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …
modular systems, such as their overwhelming complexity and propensity for error …
Hota: A higher order metric for evaluating multi-object tracking
Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics
overemphasize the importance of either detection or association. To address this, we …
overemphasize the importance of either detection or association. To address this, we …
Deep learning in video multi-object tracking: A survey
Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …
different objects in a sequence, usually a video. In recent years, with the rise of Deep …
Detection and tracking meet drones challenge
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …
range of applications, including agriculture, aerial photography, and surveillance …
Motchallenge: A benchmark for single-camera multiple target tracking
Standardized benchmarks have been crucial in pushing the performance of computer vision
algorithms, especially since the advent of deep learning. Although leaderboards should not …
algorithms, especially since the advent of deep learning. Although leaderboards should not …
Motsynth: How can synthetic data help pedestrian detection and tracking?
Deep learning-based methods for video pedestrian detection and tracking require large
volumes of training data to achieve good performance. However, data acquisition in …
volumes of training data to achieve good performance. However, data acquisition in …